ArticleDiagnostics (Basel, Switzerland)2021
Assessing Parkinson's Disease at Scale Using Telephone-Recorded Speech: Insights from the Parkinson's Voice Initiative.
Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Adaptive regression model for Parkinson's disease diagnosis from speech signals using Box-Cox-based clustering and extremely randomization.Scientific reports · 2026Article
- The Voice of Endo: Leveraging Speech for an Intelligent System That Can Forecast Illness Flare-ups.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2025Article
- Speech and language biomarkers for Parkinson's disease prediction, early diagnosis and progression.NPJ Parkinson's disease · 2025Review
- Vocal Feature Changes for Monitoring Parkinson's Disease Progression-A Systematic Review.Brain sciences · 2025Review
- An acoustic model of speech dysprosody in patients with Parkinson's disease.Frontiers in human neuroscience · 2025Article
- Digital speech assessments and machine learning for differentiation of neurodegenerative diseases.Clinical parkinsonism & related disorders · 2025Article
- New Insights into Stroke from Continuous Passively Collected Temperature and Sleep Data Using Wrist-Worn Wearables.Sensors (Basel, Switzerland) · 2023Article
- Lightweight Deep Learning Model for Assessment of Substitution Voicing and Speech after Laryngeal Carcinoma Surgery.Cancers · 2022Article
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Authors and funding
2 authors.
Funding
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Abstract
Numerous studies have reported on the high accuracy of using voice tasks for the remote detection and monitoring of Parkinson's Disease (PD). Most of these studies, however, report findings on a small number of voice recordings, often collected under acoustically controlled conditions, and therefore cannot scale at large without specialized equipment. In this study, we aimed to evaluate the potential of using voice as a population-based PD screening tool in resource-constrained settings. Using the standard telephone network, we processed 11,942 sustained vowel /a/ phonations from a US-English cohort comprising 1078 PD and 5453 control participants. We characterized each phonation using 304 dysphonia measures to quantify a range of vocal impairments. Given that this is a highly unbalanced problem, we used the following strategy: we selected a balanced subset (
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Registered trials
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